Haohao Dong

Class-Prior Perturbation-Robust Regularization for Imbalanced Unreliable Partial Label Learning

Imbalanced Unreliable Partial Label Learning (I-UPLL) is a challenging weakly supervised learning setting in which severe class imbalance and unreliable candidate labels jointly degrade model performance. By revisiting existing approaches for imbalanced learning, we observe that most of them fundame…